Two Contemporary and Efficient Two-Stage Sampling Methods for Estimating the Volume of Forest Stands: A Brief Overview and Unified Mathematical Description

Aristeidis Georgakis, G. Stamatellos
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引用次数: 2

Abstract

Big Basal Area Factor (Big BAF) and Point-3P are two-stage sampling methods. In the first stage the sampling units, in both methods, are Bitterlich points where the selection of the trees is proportional to their basal area. In the second stage, sampling units are trees which are a subset of the first stage trees. In the Big BAF method, the probability of selecting trees in the second stage is made proportional to the two BAFs’ ratio, with a basal area factor larger than that of the first stage. In the Point-3P method the probability of selecting trees, in the second stage, is based on the height prediction and use of a specific random number table. Estimates of the forest stands’ volume and their sampling errors are based on the theory of the product of two random variables. The increasing error in the second stage is small, but the total cost of measuring the trees is much smaller than simply using the first stage, with all the trees measured. In general, the two sampling methods are modern and cost-effective approaches that can be applied in forest stand inventories for forest management purposes and are receiving the growing interest of researchers in the current decade.
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两种现代有效的林分材积估算两阶段抽样方法——概述与统一数学描述
大基底面积因子(Big BAF)和Point-3P是两阶段采样方法。在第一阶段,两种方法中的采样单位都是Bitterlich点,在那里树木的选择与其基底面积成比例。在第二阶段中,采样单元是作为第一阶段树的子集的树。在大BAF方法中,第二阶段选择树木的概率与两个BAF的比率成比例,基底面积因子大于第一阶段的基底面积因子。在Point-3P方法中,在第二阶段中,选择树的概率是基于高度预测和特定随机数表的使用。林分体积及其抽样误差的估计是基于两个随机变量的乘积理论。第二阶段中增加的误差很小,但测量树木的总成本比简单地使用第一阶段(测量所有树木)要小得多。总的来说,这两种采样方法是现代且具有成本效益的方法,可用于森林管理目的的林分清查,在当前十年中受到研究人员越来越大的兴趣。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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